Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Muhammad Momin Rahman

Development of a Signal Flow Graph-Based De-Embedding Framework for Broadband Passive Linear Multiport RF & Microwave Networks with Applications to Power Splitters

When & Where:


Nichols Hall, Room 317 (Richard K. Moore Conference Room)

Committee Members:

Carl Leuschen, Chair
Kenneth Demarest
Fernando Rodriguez-Morales


Abstract

Discrete passive components, including resistors, capacitors, inductors, and transformers, are fundamental to broadband 75-Ω radio-frequency (RF) systems, particularly in cable television (CATV) and hybrid fiber-coaxial (HFC) networks. These components are incorporated into power splitters, couplers, power inserters, and amplifiers to achieve desired frequency responses, impedance matching, and signal transmission characteristics. However, their electrical behavior becomes increasingly complex at higher frequencies due to parasitic resistance, inductance, capacitance, electromagnetic coupling, and distributed transmission-line effects. Consequently, accurate broadband characterization is essential for predicting component behavior and developing representative RF circuit models for simulation purposes.

A significant challenge arises when characterizing passive components with limited or unavailable manufacturer specifications, particularly when existing component inventories must be evaluated for broadband applications. Conventional measurement instruments, including digital multimeters, LCR meters, oscilloscopes, and function generators, generally lack the frequency range required for comprehensive RF characterization from 5 MHz to 3 GHz. Vector network analyzers (VNAs) enable complex scattering-parameter measurements across this frequency range; however, the measured response includes contributions from test fixtures, interconnections, and parasitic discontinuities that must be distinguished from the intrinsic response of the device under test (DUT).

This project investigates the development of a signal flow graph (SFG)-based de-embedding framework for broadband passive linear multiport RF networks. The methodology incorporates series-through and shunt-through DUT (CPWG) fixture configurations, conventional Open-Short and Short-Open de-embedding techniques, followed by lumped-element and distributed transmission-line representations of fixture parasitics. Scattering-parameter and ABCD-parameter analysis are employed to characterize fixture responses, while signal flow graph derivations provide a mathematical basis for analyzing interconnected multiport networks. Particular attention is given to fixture asymmetry, impedance discontinuities, and multiple signal propagation paths that complicate the extension of conventional two-port characterization methods to higher-order networks.

Experimental validation is conducted through the characterization of passive components with published impedance and quality-factor characteristics, enabling comparisons between extracted measurements, equivalent-circuit models, and manufacturer reference data. The methodology is subsequently applied to broadband power splitter networks used in CATV/HFC systems to investigate the accuracy and applicability of the proposed multiport de-embedding framework. The project aims to establish a systematic approach to broadband passive component characterization that integrates fixture modeling, network theory, and experimental measurement while reducing dependence on proprietary characterization data.


Fairuz Shadmani Shishir

Efficient and Privacy-Preserving Biomedical AI: From Precision Therapeutics Design to Private Clinical Prediction

When & Where:


Eaton Hall, Room 2001B

Committee Members:

Sumaiya Shomaji, Chair
Tamzidul Hoque
Cuncong Zhong
Bishnu Sarker
Michael Hageman

Abstract

Accurate protein characterization, precision therapeutics design, and privacy-preserving clinical modeling are important challenges in biomedical artificial intelligence (AI). Addressing these challenges requires computational frameworks that are not only accurate and scalable but also capable of supporting reliable decision-making. This dissertation develops efficient, scalable, and reliable computational frameworks across three areas: Computational characterization of proteins, precision therapeutics design, and privacy-aware clinical representation learning. The first part of this dissertation focuses on efficient protein characterization at both the sequence and residue levels. GPCR-SLM, a knowledge-distilled small protein language model, classifies G-protein-coupled receptors (GPCRs), a family targeted by approximately 35% of FDA-approved drugs. Across 86 families, GPCR-SLM achieves 99% accuracy, outperforming BLAST (86.4%) and HMMER (91%), with a 33.5-fold speedup over large protein language models. Extending characterization to the residue level, a protein-metal-ion binding site prediction framework evaluates five protein language models and incorporates positional encoding to capture long-range dependencies. Under 10-fold cross-validation, it achieves a Matthews correlation coefficient of 0.89, with precision, recall, and F1 scores exceeding 95% across six metal ions.

Building on these protein characterization methods, the second part advances precision therapeutics design through uncertainty quantification and generative learning for therapeutic antibodies. NbBayesLM combines protein language model embeddings and physicochemical descriptors in a Bayesian neural network to predict nanobody thermostability. Evaluated on 10,630 VHH sequences, it achieves a mean absolute error of 1.89C and an R2 of 0.67 while estimating epistemic and aleatoric uncertainty to support candidate prioritization. CIgFlow employs classifier-free guidance to generate de novo, antigen-conditioned antibody sequences without fixed scaffolds or paired structural data. Generated sequences achieve a median OASis humanness score of 0.90 and mean predicted local distance difference test (pLDDT) score of 85.0, demonstrating promising novelty and diversity. The third part addresses privacy-aware clinical modeling using electrocardiograms (ECGs), which encode diagnostic information and sensitive demographic attributes. A variational autoencoder with dual discriminators suppresses demographic information while preserving clinically relevant representations.

Collectively, this dissertation advances efficient protein representation learning, computational antibody design, and privacy-preserving clinical AI, contributing methodological foundations for trustworthy biomedical applications.


Arturo Solorio

Performance Analysis of Mismatched Filtering for Stochastic Waveforms

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Patrick McCormick, Chair
Shannon Blunt
Charles Mohr


Abstract

Mismatched filtering (MMF) is a widely used pulse compression technique that reduces cross-correlation sidelobe levels at the cost of some loss in signal-to-noise ratio (SNR). Applying MMF to stochastically generated radar waveforms makes the filter's performance inherently random, which can be problematic if the variability is excessive. As well as the computational cost being relatively high, as per pulse, a new MMF optimization is required. In this thesis, the feasibility of a fixed MMF strategy for stochastic radar waveforms to reduce computational cost is investigated. Two MMF formulations were evaluated, the optimal MMF (Diagonal Loaded Filter) and a projection-based MMF. Both filters were designed to minimize sidelobe energy within specified regions of the Cross-Ambiguity Function (CAF) for Stochastic Waveform Generation (StoWGe) waveforms, and their performance was assessed across multiple time-bandwidth products and sidelobe-regions for two center frequencies, Fc = 30 Ghz and Fc  = 3.5 Ghz. The MMF performance was characterized using SNR loss and sidelobe depth over hundreds of trails. It is observed that the variability in SNR and sidelobe depth decreases as the waveform time-bandwdith product and the sidelobe region targeted for minimization increase, although the Fc = 3.5 GHz cases exhibited a plateau in achievable sidelobe depth. Additional validation using 1000-trail histograms and loop-back testing confirmed the robustness for the fixed MMF approach for higher time-bandwidth product stochastic waveforms. Where, overall, the results demonstrate that a fixed MMF strategy is feasible for stochastic waveforms when the time-bandwdith product and sidelobe region are sufficiently large. Furthermore, the Projection-based MMF provides a suboptimal alternative to the optimal MMF as it achieves comparable MMF performance when constrained to similar SNR-loss and may be desirable when the size of the domination eigenvalues is small relative to the filter length and can be efficiency obtained.


Past Defense Notices

Dates

SRI HARSHA KOMARINA

System Logging and Analysis using Time Series Databases

When & Where:


2001B Eaton Hall

Committee Members:

Joseph Evans, Chair
Prasad Kulkarni
Bo Luo


Abstract

Logging system information and its metrics provides us with a valuable resource to monitor the system for unusual activity and understand the various factors affecting its performance. Though there are several tools that are available to log and analyze the system locally, it is inefficient to individually analyze every system and is seldom effective in case of hardware failure. Having centralized access to this information aids the system administrators in performing their operational tasks. Here we present a centralized logging solution for system logs and metrics by using Time Series Databases (TSDB). We provide reliable storage and efficient access to system information by storing the parsed system logs and metrics in a TSDB. In this project, we develop a solution to store the system’s default log storage - syslog as well as the system metrics like CPU load, disk load, and network traffic load into a TSDB. We further extend our ability to monitor and analyze the data in our TSDB by using an open source graphing tool. 


EVAN AUSTIN

Theorem Provers as Libraries — An Approach to Formally Verifying Functional Programs

When & Where:


246 Nichols Hall

Committee Members:

Perry Alexander, Chair
Arvin Agah
Andy Gill
Prasad Kulkarni
Erik Van Vleck

Abstract

Property-directed verification of functional programs tends to take one of two paths. 
First, is the traditional testing approach, where properties are expressed in the original programming language and checked with a collection of test data. 
Alternatively, for those desiring a more rigorous approach, properties can be written and checked with a formal tool; typically, an external proof system. 
This dissertation details a hybrid approach that captures the best of both worlds: the formality of a proof system paired with the native integration of an embedded, domain specific language (EDSL) for testing. 

At the heart of this hybridization is the titular concept -- \emph{a theorem prover as a library}. 
The verification capabilities of this prover, HaskHOL, are introduced to a Haskell development environment as a GHC compiler plugin. 
Operating at the compiler level provides for a comparatively simpler integration and allows verification to co-exist with the numerous other passes that stand between source code and program. 

The logical connection between language and proof library is formalized, and the open problems related to this connection are documented. 
Additionally, the resultant, novel verification workflow is applied to two major classes of problems, type class laws and polymorphic test cases, to judge the real-world feasibility of compiler-directed verification. 
These applications and formalization serve to position this work relative to existing work and to highlight potential, future extensions.


CAMERON LEWIS

Ice Shelf Melt Rates and 3D Imaging

When & Where:


317 Nichols Hall

Committee Members:

Prasad Kulkarni, Chair
Chris Allen
Carl Leuschen
Fernando Rodriguez-Morales
Rick Hale

Abstract

Ice shelves are sensitive indicators of climate change and play a critical role in the stability of ice sheets and oceanic currents. Basal melting of ice shelves plays an important role in both the mass balance of the ice sheet and the global climate system. Airborne- and satellite based remote sensing systems can perform thickness measurements of ice shelves. Time separated repeat flight tracks over ice shelves of interest generate data sets that can be used to derive basal melt rates using traditional glaciological techniques. Many previous melt rate studies have relied on surface elevation data gathered by airborne- and satellite based altimeters. These systems infer melt rates by assuming hydrostatic equilibrium, an assumption that may not be accurate, especially near an ice shelf’s grounding line. Moderate bandwidth, VHF, ice penetrating radar has been used to measure ice shelf profiles with relatively coarse resolution. This study presents the application of an ultra wide bandwidth (UWB), UHF, ice penetrating radar to obtain finer resolution data on the ice shelves. These data reveal significant details about the basal interface, including the locations and depth of bottom crevasses and deviations from hydrostatic equilibrium. While our single channel radar provides new insight into ice shelf structure, it only images a small swatch of the shelf, which is assumed to be an average of the total shelf behavior. This study takes an additional step by investigating the application of a 3 D imaging technique to a data set collected using a ground based multi channel version of the UWB radar. The intent is to show that the UWB radar could be capable of providing a wider swath 3 D image of an ice shelf. The 3 D images can then be used to obtain a more complete estimate of bottom melt rates of ice shelves.


RALPH BAIRD

Isomorphic Routing Protocol

When & Where:


250 Nichols Hall

Committee Members:

Victor Frost, Chair
Bo Luo
Hossein Saiedian


Abstract

A mobile ad-hoc network (MANET) routing algorithm defines the path packets take to reach their destination using measurements of attributes such as adjacency and distance. Graph theory is increasingly applied in many fields of research today to model the properties of data on a graph plane. Graph theory is applied to in networking to form structures from patterns of nodes. Conventional MANET protocols are often based on path measurements from wired network algorithms and do not implement mechanisms to mitigate route entropy, defined as the procession of a converged path to a path loss state as a result of increasing random movement. Graph isomorphism measures equality beginning in the individual node and in sets of nodes and edges. The measurement of isomorphism is applied in this research to form paths from an aggregate set of route inputs, such as adjacency, cardinality to impending nodes in a path, and network width. A routing protocol based on the presence of isomorphism in a MANET topology is then tested to measure the performance of the proposed routing protocol.


DAIN VERMAAK

Application of Half Spaces in Bounding Wireless Internet Signals for use in Indoor Positioning

When & Where:


246 Nichols Hall

Committee Members:

Joseph Evans, Chair
Jim Miller
Gary Minden


Abstract

The problem of outdoor positioning has been largely solved via the use of GPS. This thesis addresses the problem of determining position in areas where GPS is unavailable. No clear solution exists for indoor localization and all approximation methods offer unique drawbacks. To mitigate the drawbacks, robust systems combine multiple complementary approaches. In this thesis, fusion of wireless internet access points and inertial sensors was used to allow indoor positioning without the need for prior information regarding surroundings. Implementation of the algorithm involved development of three separate systems. The first system simply combines inertial sensors on the Android Nexus 7 to form a step counter capable of providing marginally accurate initial measurements. Having achieved reliable initial measurements, the second system receives signal strength from nearby wireless internet access points, augmenting the sensor data in order to generate half-planes. The half-planes partition the available space and bound the possible region in which each access point can exist. Lastly, the third system addresses the tendency of the step counter to lose accuracy over time by using the recently established positions of the access points to correct flawed values. The resulting process forms a simple feedback loop.


ANDREW FARMER

HERMIT: Mechanized Reasoning during Compilation in the Glasgow Haskell Compiler

When & Where:


250 Nichols Hall

Committee Members:

Andy Gill, Chair
Perry Alexander
Prasad Kulkarni
Jim Miller
Chris Depcik

Abstract

It is difficult to write programs which are both correct and fast. A promising approach, functional programming, is based on the idea of using pure, mathematical functions to construct programs. With effort, it is possible to establish a connection between a specification written in a functional language, which has been proven correct, and a fast implementation, via program transformation. 

When practiced in the functional programming community, this style of reasoning is still typically performed by hand, by either modifying the source code or using pen-and-paper. Unfortunately, performing such semi-formal reasoning by directly modifying the source code often obfuscates the program, and pen-and-paper reasoning becomes outdated as the program changes over time. Even so, this semi-formal reasoning prevails because formal reasoning is time-consuming, and requires considerable expertise. Formal reasoning tools often only work for a subset of the target language, or require programs to be implemented in a custom language for reasoning. 

This dissertation investigates a solution, called HERMIT, which mechanizes reasoning during compilation. HERMIT can be used to prove properties about programs written in the Haskell functional programming language, or transform them to improve their performance. 
Reasoning in HERMIT proceeds in a style familiar to practitioners of pen-and-paper reasoning, and mechanization allows these techniques to be applied to real-world programs with greater confidence. HERMIT can also re-check recorded reasoning steps on subsequent compilations, enforcing a connection with the program as the program is developed. 

HERMIT is the first system capable of directly reasoning about the full Haskell language. The design and implementation of HERMIT, motivated both by typical reasoning tasks and HERMIT's place in the Haskell ecosystem, is presented in detail. Three case studies investigate HERMIT's capability to reason in practice. These case studies demonstrate that semi-formal reasoning with HERMIT lowers the barrier to writing programs which are both correct and fast. 


JAY McDANIEL

Design, Integration, and Miniaturization of a Multichannel Ultra-Wideband Snow Radar Receiver and Passive Microwave Components

When & Where:


129 Nichols

Committee Members:

Carl Leuschen, Chair
Stephen Yan
Prasad Gogineni


Abstract

To meet the demand for additional snow characterization from the Intergovernmental Panel on Climate Change (IPCC), a new “Airborne” Multichannel, Quad-Polarized 2-18GHz Snow Radar has been proposed. With tight size and weight constraints from the airborne platforms deploying with the Navy Research Laboratory (NRL), the need for integrated and miniaturized receivers for cost and size reduction is crucial for future deployments. 

A set of heterodyne microwave receivers were developed to enable snow thickness measurements from a survey altitude of 500 feet to 5000 feet while nadir looking, and estimation of SWE from polarimetric backscattered signals at low elevation 30 degree off nadir. The individual receiver has undergone a five times size reduction with respect to initial prototype design, while achieving a sensitivity of -125 dBm on average across the 2-18 GHz bandwidth, enabling measurements with a vertical range resolution of 1.64 cm in snow. The design of a compact enclosure was defined to accommodate up to 18 individual receiver modules allowing for multichannel quad-polarized measurements over the entire 16 GHz bandwidth. The receiver bank was tested individually and with the entire system in a full multichannel loop-back measurement, using a 2.95 μs optical delay line, resulting in a beat frequency of 200 MHz with 20 dB range side lobes. Due to the multi-angle, multi-polarization, and multi-frequency content from the data , the number of free parameters in the SWE estimation can thus be significantly reduced. 

Design equations have been derived and a new method for modeling Suspended Substrate Stripline (SSS) filters in ADS for rapid-prototyping has been accomplished. Two SSS filters were designed which include an Optimized Chebyshev SSS Low Pass Filter (LPF) with an 18 GHz cutoff frequency and a Broadside Coupled SSS High Pass Filter (HPF) with a 2 GHz cutoff frequency. Also, a 2-18 GHz three-port Transverse Electromagnetic (TEM) Mode Hybrid 8:1 power combiner was designed and modeled at CReSIS. This design will be integrated into the Vivaldi Dual Polarized antenna array with 8 active dual-polarized elements to implement a lightweight and compact array structure, eliminating cable and connector cost and losses. 


VADIRAJ HARIBAL

Modelling of ATF-38143 P-HEMT Driven Resistive Mixer for VHF KNG P-150 Portable Radios

When & Where:


250 Nichols Hall

Committee Members:

Ron Hui, Chair
Chris Allen
Alessandro Salandrino


Abstract

FET resistive mixers play a key role in providing high linearity and low noise figure levels. HEMT technology with low threshold voltage has popularized mobile phone market and milli-meter wave technologies. The project analyzes working of a down-conversion VHF FET resistive mixer model designed using ultra-low noise ATF -38143 P-HEMT. Its widely used in KNG-P150 portable mobile radios manufactured by RELM Wireless Corporation. The mixer is designed to function within RF frequency range from 136Mhz -174Mhz at an IF frequency of 51.50Mhz. Statz model has been used to simulate the working of P-HEMT under normal conditions. Transfer function of matching circuits at each port have been obtained using simulink modelling. Effect of change in Q factor at the RF port and IF port have been considered. Analytical modelling of the mixer is performed and simulated results are compared with experimental data obtained at constant 5dbm LO power. IF transfer function has been modelled to closely match the practical circuits by applying adequate amplitude damping to the response of LC circuits at the RF port, in order to provide the required IF bandwidth and conversion gain. Effect of stray capacitances and inductances have been neglected during the modelling, and changes in series resistance of inductors at RF port and IF port have been made to match experimental results.


MOHAMMED ALENAZI

Network Resilience Improvement and Evaluation Using Link Additions

When & Where:


246 Nichols Hall

Committee Members:

James Sterbenz, Chair
Victor Frost
Lingjia Liu
Bo Luo
Tyrone Duncan

Abstract

Computer networks are getting more involved in providing services for most of our daily life activities related to education, business, health care, social life, and government. Publicly available computer networks are prone to targeted attacks and natural disasters that could disrupt normal operation and services. Building highly resilient networks is an important aspect of their design and implementation. For existing networks, resilience against such challenges can be improved by adding more links. In fact, adding links to form a full mesh yields the most resilient network but it incurs an unfeasible high cost. In this research, we investigate the resilience improvement of real-world networks via adding a cost-efficient set of links. Adding a set of links to obtain optimal solution using an exhaustive search is impracticable for large networks. Using a greedy algorithm, a feasible solution is obtained by adding a set of links to improve network connectivity by increasing a graph robustness metric such as algebraic connectivity or total path diversity. We use a graph metric called flow robustness as a measure for network resilience. To evaluate the improved networks, we apply three centrality-based attacks and study their resilience. The flow robustness results of the attacks show that the improved networks are more resilient than the non-improved networks. 


WENRONG ZENG

Content-Based Access Control

When & Where:


250 Nichols Hall

Committee Members:

Bo Luo, Chair
Arvin Agah
Jerzy Grzymala-Busse
Prasad Kulkarni
Alfred Tat-Kei

Abstract

In conventional database, the most popular access control model specifies policies explicitly for each role of every user against each data object manually. Nowadays, in large-scale content-centric data sharing, conventional approaches could be impractical due to exponential explosion of the data growth and the sensitivity of data objects. What’s more, conventional database access control policy will not be functional when the semantic content of data is expected to play a role in access decisions. Users are often over-privileged, and ex post facto auditing is enforced to detect misuse of the privileges. Unfortunately, it is usually difficult to reverse the damage, as (large amount of) data has been disclosed already. In this dissertation, we first introduce Content-Based Access Control (CBAC), an innovative access control model for content-centric information sharing. As a complement to conventional access control models, the CBAC model makes access control decisions based on the content similarity between user credentials and data content automatically. In CBAC, each user is allowed by a meta-rule to access "a subset" of the designated data objects of a content-centric database, while the boundary of the subset is dynamically determined by the textual content of data objects. We then present an enforcement mechanism for CBAC that exploits Oracles Virtual Private Database (VPD) to implement a row-wise access control and to prevent data objects from being abused by unneccessary access admission. To further improve the performance of the proposed approach, we introduce a content-based blocking mechanism to improve the efficiency of CBAC enforcement to further reveal a more relavant part of the data objects comparing with only using the user credentials and data content. We also utilized several tagging mechanisms for more accurate textual content matching for short text snippets (e.g. short VarChar attributes) to extract topics other than pure word occurences to represent the content of data. In the tagging mechanism, the similarity of content is calculated not purely dependent on the word occurences but the semantic topics underneath the text content. Experimental results show that CBAC makes accurate access control decisions with a small overhead.